Mining of Mineral Deposits

ISSN 2415-3443 (Online)

ISSN 2415-3435 (Print)

Flag Counter

Risk criteria classification and the evaluation of blasting operations in open pit mines by using the FDANP method

Mohammad Kian1, Seyed Hamid Hosseini1, Mohammad Taji2, Mehran Gholinejad,1,3

1South Tehran Branch, Islamic Azad University, Tehran, 1777613651, Iran

2Shahroud Branch, Islamic Azad University, Shahroud, 3619943189, Iran

3Research Center for Modeling and Optimization in Science and Engineering, South Tehran Branch, Islamic Azad University, Tehran, 1777613651, Iran


Min. miner. depos. 2021, 15(2):70-81


https://doi.org/10.33271/mining15.02.070

Full text (PDF)


      ABSTRACT

      Purpose. Mineral projects are heavily influenced by risk factors. By providing evidence-based information and analysis to make informed decisions about how to choose between options, a risk assessment can be made.

      Methods. In this study, the relationships of 46 criteria and 10 dimensions affecting the risk of blasting operations were investigated in order to determine the significance, effectiveness, relative weight of the criteria and dimensions as well as to prioritize the risk criteria of blasting operations. For this purpose, the combination of the FDEMATEL method and FANP method are used as FDANP.

      Findings. The most important criterion is the lack of specialized knowledge (C1). The damage to manpower criterion (C46) will receive the greatest impact from other criteria. The criterion for implementing the explosion plan, without respecting the design principles (C12) has most interactions with other criteria and the failure to determine the amount of production capacity (low or high) criterion (C45) has the least interactions with other criteria. According to the FDANP method, the number of explosions in one stage (C14) is the first criterion of the blasting operations risk.

      Originality. By controlling this criterion, the effects and destructive consequences of blasting operations can be prevented. Controlling this criterion reduces the risk of blasting operations and also reduces the damage by C46 criterion. From comparison, human resources dimension (D1) is the most effective and natural hazards dimension (D10) has the greatest interactions with other dimensions and is most affected among the other dimensions. The production and extraction consideration dimension (D9) has the least interaction with other dimensions and is less important.

      Practical implications. By reducing the destructive effects of blasting operations, two favorable results will be achieved: the reduction of damage caused by undesirable consequences and the assignment of a greater share of blast energy to the desired outcomes.

      Keywords: blasting evaluation, blasting operation, open pit mine, FDANP method


      REFERENCES

  1. Paithankar, A. (2011). Hazard identification and risk analysis in mining industry. A thesis submitted in partial fulfillment of the requirements for the degree of bachelor of technology in mining engineering. National Institute of Technology Rourkela, Department of Mining Engineering, India.
  2. Taji, M. (2008). The classification of open pit mine blast results by BBSR. Proceedings of the 1 the National Symposium on Blasting Engineering and Industrial Explosives, 1-6.
  3. Taji, M., Ataei, M., Goshtasbi, K., & Osanloo, M. (2012). ODM: A new approach for open pit mine blasting evaluation. Journal of Vibration and Control, 19(11), 1738-1752. https://doi.org/10.1177/1077546312439911
  4. Monjezi, M., Bahrami, A., Varjani, A.Y., & Sayadi, A.R. (2011). Prediction and controlling of flyrock in blasting operation using artificial neural network. Arabian Journal of Geosciences, 4(3-4), 421-425. https://doi.org/10.1007/s12517-009-0091-8
  5. Armaghani, D.J., Hajihassani, M., Mohamad, E.T., Marto, A., & Noorani, S.A. (2013). Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization. Arabian Journal of Geosciences, 7(12), 5383-5396. https://doi.org/10.1007/s12517-013-1174-0
  6. Sayadi, A., Monjezi, M., Talebi, N., & Khandelwal, M. (2013). A comparative study on the application of various artificial neural networks to simultaneous prediction of rock fragmentation and backbreak. Journal of Rock Mechanics and Geotechnical Engineering, 5(4), 318-324. https://doi.org/10.1016/j.jrmge.2013.05.007
  7. Saadat, M., Khandelwal, M., & Monjezi, M. (2014). An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine, Iran. Journal of Rock Mechanics and Geotechnical Engineering, 6(1), 67-76. https://doi.org/10.1016/j.jrmge.2013.11.001
  8. Marto, A., Hajihassani, M., Jahed Armaghani, D., Tonnizam Mohamad, E., & Makhtar, A.M. (2014). A novel approach for blast-induced flyrock prediction based on imperialist competitive algorithm and artificial neural network. The Scientific World Journal, (2014), 1-11. https://doi.org/10.1155/2014/643715
  9. Trivedi, R., Singh, T.N., & Raina, A.K. (2014). Prediction of blast-induced flyrock in Indian limestone mines using neural networks. Journal of Rock Mechanics and Geotechnical Engineering, 6(5), 447-454. https://doi.org/10.1016/j.jrmge.2014.07.003
  10. Faramarzi, F., Mansouri, H., & Ebrahimi Farsangi, M.A. (2013). A rock engineering systems based model to predict rock fragmentation by blasting. International Journal of Rock Mechanics and Mining Sciences, (60), 82-94.https://doi.org/10.1016/j.ijrmms.2012.12.045
  11. Faramarzi, F., Mansouri, H., & Farsangi, M.A.E. (2014). Development of rock engineering systems-based models for flyrock risk analysis and prediction of flyrock distance in surface blasting. Rock Mechanics and Rock Engineering, 47(4), 1291-1306. https://doi.org/10.1007/s00603-013-0460-1
  12. Singh, P.K., Roy, M.P., Paswan, R.K., Sarim, M.D., Kumar, S., & Ranjan Jha, R. (2016). Rock fragmentation control in opencast blasting. Journal of Rock Mechanics and Geotechnical Engineering, (8), 225-237. https://doi.org/10.1016/j.jrmge.2015.10.005
  13. Ghaeini, N., Mousakhani, M., Amnieh, H.B., & Jafari, A. (2017). Prediction of blasting-induced fragmentation in Meydook copper mine using empirical, statistical, and mutual information models. Arabian Journal of Geosciences, 10(18), 23-28. https://doi.org/10.1007/s12517-017-3189-4
  14. Ghasemi, E. (2017). Particle swarm optimization approach for forecasting backbreak induced by bench blasting. Neural Computing and Applications, 28(7), 1855-1862. https://doi.org/10.1007/s00521-016-2182-2
  15. Yari, M., Bagherpour, R., & Jamali, S. (2017). Development of an evaluation system for blasting patterns to provide efficient production. Journal of Intelligent Manufacturing, 28(4), 975-984. https://doi.org/10.1007/s10845-015-1036-6
  16. Li, C.W., & Tzeng, G.H. (2009). Identification of a threshold value for the DEMATEL method using the maximum mean deentropy algorithm to find critical services provided by a semiconductor intellectual property mall. International Journal of Expert Systems with Applications, 8(1), 9891-989. https://doi.org/10.1012/j.eswa.2009.01.073
  17. Vujanovic, D., Momcilovic, V., Bojovic, N., & Papic, V. (2012). Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP. Expert Systems with Applications, 39(12), 10552-10563. https://doi.org/10.1016/j.eswa.2012.02.159
  18. Saaty, T.L. (1996). The analytic network process. Arlington, United State: RWS Publications, Expert Choice, Inc.
  19. Saaty, T.L. (2006). Rank from comparisons and from ratings in the analytic hierarchy/network processes. European Journal of Operational Research, 168(2), 557-570.https://doi.org/10.1016/j.ejor.2004.04.032
  20. Lee, W.S., Yi Hou Huang, A., Chang, Y.Y., & Cheng, C.M. (2011). Analysis of decision making factors for equity investment by DEMATEL and Analytic Network Process. International Journal of Expert Systems with Applications, 38(7), 8375-8383. https://doi.org/10.1016/j.eswa.2011.01.027
  21. Gabus, A., & Fontela, E. (1972). World problems an invitation to further thought within the framework of DEMATEL. Geneva, Switzerland: Battelle Geneva Research Centre.
  22. Gabus, A., & Fontela, E. (1973). Perceptions of the world problematique: Communication procedure communicating.
  23. Wu, W.W. (2008). Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Systems with Applications, 35(3), 828-835. https://doi.org/10.1016/j.eswa.2007.07.025
  24. Ou Yang, Y.P., Shieh, H.M., & Tzeng, G.H. (2013). A VIKOR technique based on DEMATEL and ANP for information security risk control assessment. Information Sciences, 232(2013), 482-500. https://doi.org/10.1016/j.ins.2011.09.012
  25. Dagdeviren, M., & Yuksel, I. (2010). A fuzzy analytic network process (ANP) model for measurement of the sectoral competition level (SCL). Expert Systems with Applications, 37(2), 1005-1014. https://doi.org/10.1016/j.eswa.2009.05.074
  26. Chou, T.-Y., Hsu, C.-L., & Chen, M.-C. (2008). A fuzzy multi-criteria decision model for international tourist hotels location selection. International Journal of Hospitality Management, 27(2), 293-301.
  27. Zadeh, L.A. (1975). The concept of a linguistic variable and its ap plication to approximate reasoning. Information Sciences, 8(4), 199-249. https://doi.org/10.1016/0020-0255(75)90046-8
  28. Li, R.J. (1999). Fuzzy method in group decision making. Computers and Mathematics with Applications, 38(1), 91-101. https://doi.org/10.1016/S0898-1221(99)00172-8
  29. Lee, H.S., Tzeng, G.H., Yeih, W., Wang, Y.J., & Yang, S.C. (2013). Revised DEMATEL: Resolving the Infeasibility of DEMATEL. Applied Mathematical Modelling, 37(2013), 6746-6757. https://doi.org/10.1012/j.apm.2013.01.016
  30. Kuan, M.J., & Chen, Y.M. (2014). A hybrid MCDM framework combined with DEMATEL-based ANP to evaluate enterprise technological innovation capabilities assessment. Decision Science Letters, 3(4), 491-502. https://doi.org/10.5267/j.dsl.2014.6.003

    31. Лицензия Creative Commons

Copyright © 2024 Dnipro University of Technology

Underground Mining Department

All Rights Reserved.

Journal homepage Authors